Robot space continuous curve trajectory offline programming method, storage medium and system

Abstract

The present invention discloses a robot space continuous curve trajectory offline programming method, storage medium and system. The method is: after the three-dimensional model of the robot and the material to be processed is imported into the three-dimensional simulation software, the software is made to draw the processing trajectory; the software is made to use the robot back calculation mechanism solver to solve the point set of the trajectory; the accuracy requirement is determined according to the production process of the material to be processed, and the point taking time period is determined accordingly; Y points are taken out from the point set and stored in the target point set; the curvature of the processing trajectory at the Y points is calculated respectively, if the point curvature is less than the first threshold, the point is removed, if the point curvature is greater than the second threshold, then n points are taken out from the point set before and after the point and stored in the target point set; the target point set is output. The method can select the points of the processing trajectory according to the production process accuracy requirement standards of different materials to be processed, so as to adjust the processing accuracy of the robot accordingly.

Description

Technical Field

[0001] The invention relates to the technical field of robot off-line programming, and in particular to a robot space continuous curve trajectory off-line programming method, storage medium and system. Background Art

[0002] With the development of mechanical automation technology, many manufacturers currently use robot automation equipment, that is, to change ordinary production lines into mechanical automation production lines to realize the automated production of industrial products. This greatly reduces labor costs and improves production efficiency. A mechanical automation production line is usually not limited to the production of one product, and the products produced can be adjusted according to product order requirements. Different products have different shapes, structures, processing positions / processing trajectories, processing methods, etc. Therefore, each time the product to be produced is changed, the robot needs to be taught according to the production requirements of the new product. The traditional teaching method is manual teaching. The operator needs to pause the production line, and then manually operate the robot to perform production teaching operations on the new product according to the production requirements of the new product. The robot controller automatically records the posture data of each point of the robot end effector involved in the teaching process, and uses its own robot program language to convert the posture data of each point into a robot control program for storage. The subsequent robot controller can execute the robot control program to control the robot for automated production. Manual teaching requires pausing the production line, which will affect the production efficiency of the production line. To this end, technical personnel in the industry have proposed an offline programming method, which is to build a three-dimensional simulation model of the robot and a three-dimensional simulation model of the new product to be produced in a three-dimensional virtual simulation environment. In the three-dimensional virtual simulation environment, according to the production requirements of the new product, the three-dimensional simulation model of the robot simulates the production action of the three-dimensional simulation model of the new product. In this way, teaching is performed to obtain the posture data of each point involved in the production process of the robot end effector, and then the posture data of each point is converted into the corresponding robot control program using the special program language of the robot on the production line, and the robot control program is output. The technician then transmits the robot control program to the robot controller of the mechanical automation production line, and the robot controller can execute the robot control program to control the robot on the production line for automated production. By using the offline programming method, you can use the three-dimensional simulation software for teaching in advance, and you can start producing new products after the production line has finished producing old products, without pausing the production line for teaching. However, for product production processes whose machining trajectories are continuous trajectories in space, different processes have different requirements for precision. When the existing offline programming methods determine the point position data of different product production processes, the points are selected according to a unified standard, so the robot's machining precision is the same. But in fact, some production processes have lower requirements for the robot's machining precision. Higher machining precision requirements will reduce the robot's production efficiency. Summary of the invention

[0003] The purpose of the present invention is to provide a robot spatial continuous trajectory offline programming method, a computer-readable storage medium storing a computer program that implements the method when executed, and an offline programming system that can execute the method. The method can select the points of the processing trajectory according to the production process accuracy requirements of different materials to be processed, thereby adjusting the processing accuracy of the robot accordingly.

[0004] In order to achieve the above object, the present invention provides a robot space continuous curve trajectory offline programming method, the method is executed by PLC, and specifically includes the following steps:

[0005] S1. After the robot 3D model and the 3D model of the material to be processed are imported into the 3D simulation software, the 3D simulation software is used to draw the processing trajectory of the 3D model of the material to be processed according to the 3D model and processing requirements of the material to be processed, and the processing trajectory is a continuous curve trajectory in space;

[0006] S2. The 3D simulation software uses the robot back-calculation mechanism solver to solve the point set corresponding to the robot 3D model walking along the above processing trajectory, the point set includes X points and their point information, where X>2, and the point information includes the position coordinates, the time point when the end effector of the robot 3D model reaches the point, and the posture data of the joints and the end effector when the end effector of the robot 3D model reaches the point;

[0007] S3. Determine the accuracy requirements of the production process of the material to be processed, and determine the time period of the point of the processing trajectory;

[0008] S4. According to the above-mentioned point-taking time period, Y points and their point information are taken from the point set in the three-dimensional simulation software and stored in the target point set in the PLC, where Y <X;

[0009] S5. Calculate the curvature of the machining trajectory at the above Y points. If the curvature of the point is less than the first threshold, remove the point from the target point set. If the curvature of the point is greater than the second threshold, take n points before and after the point from the point set in the three-dimensional simulation software according to the preset point density and store them in the target point set in the PLC, where n≥1.

[0010] S6. Output the target point set as a processing trajectory point set so that the PLC can control the robot to perform actual processing operations according to the processing trajectory point set.

[0011] Further:

[0012] The method includes step S60 executed before step S6. According to the target point set, a control instruction is output to the robot three-dimensional model in the three-dimensional simulation software to simulate the processing process, and then the three-dimensional simulation software is made to measure the deviation between the trajectory of the processing process and the above processing trajectory and determine whether the deviation meets the above accuracy requirement. If it meets the above accuracy requirement, step S6 is executed, otherwise:

[0013] S7. Shorten the point-taking time period and increase the point-taking density according to the preset adjustment rules, and re-execute steps S4 to S60.

[0014] Furthermore, step S6 specifically transmits the processing trajectory point set to a PLC that controls the movement of the physical robot corresponding to the robot three-dimensional model through wireless communication.

[0015] Further, the method includes step P. receiving a production process accuracy relationship table and a point-taking time cycle rule, wherein the production process accuracy relationship table includes a correspondence between each production process and the accuracy requirement, and the point-taking time cycle rule includes a point-taking time cycle corresponding to various accuracy requirements;

[0016] Specifically, step S3 queries the precision requirement corresponding to the production process of the material to be processed from the above production process precision relationship table, and then queries the point-taking time period corresponding to the precision requirement from the point-taking time period rule.

[0017] Furthermore, the first threshold is 0.01, and the second threshold is 0.05.

[0018] The present invention also provides a computer-readable storage medium on which an executable computer program is stored. The computer program is executed to implement the above-mentioned robot spatial continuous curve trajectory offline programming method.

[0019] The present invention also provides a robot space continuous curve trajectory offline programming system, including a PLC and a client that can run three-dimensional simulation software. The PLC is communicated with the client to send control instructions to the three-dimensional simulation software. The PLC includes a central processing unit and the computer-readable storage medium as described above. The central processing unit of the PLC executes the computer program in the storage medium to implement the robot space continuous curve trajectory offline programming method as described above.

[0020] The above-mentioned robot space continuous curve trajectory offline programming method first draws the processing trajectory of the material to be processed through step S2, then executes step S2 to solve the point set (initial point set) of the processing trajectory, and then determines the point-taking time period corresponding to the precision requirement of the material to be processed by step S3. The higher the precision requirement, the shorter the point-taking time period should be (the shorter the point-taking time period, the more points are taken), and then executes step S4, that is, according to the point-taking time period determined by step S3, selects some points and their point information from the above-mentioned initial point set in the three-dimensional simulation software to obtain the target point set (the first point selection), and then executes step S5 to perform a second point selection based on the target point set to update the target point set, and finally executes step S6 to output the target point set for the PLC to control the robot to perform actual processing operations according to the processing trajectory point set. This method S3 selects the point-taking time period of the processing trajectory points according to the production process precision requirement standards of different materials to be processed, so as to achieve the corresponding adjustment of the robot's processing accuracy. In this way, for materials to be processed with higher precision requirements, the points of the processing trajectory are increased accordingly to improve the processing accuracy of the robot. For materials to be processed with lower precision requirements, the points of the processing trajectory are reduced accordingly to reduce the processing accuracy of the robot. In this way, maximum production efficiency can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is the structural block diagram of the robot space continuous curve trajectory offline programming system.

[0022] Figure 2 It is a flow chart of the offline programming method of the robot's spatial continuous curve trajectory. DETAILED DESCRIPTION

[0023] The present invention is further described in detail below in conjunction with specific implementation methods.

[0024] like Figure 1 As shown, the robot space continuous curve trajectory offline programming system (hereinafter referred to as offline programming system) includes a PLC and a client that can run a three-dimensional simulation software. The PLC is connected to the client to send control instructions to the three-dimensional simulation software. The PLC includes a central processing unit and a computer-readable storage medium. The central processing unit of the PLC executes the computer program in the storage medium to achieve the following Figure 2 The offline programming method of the robot spatial continuous curve trajectory is shown.

[0025] In order to perform offline programming of the robot's spatial continuous curve trajectory, the user needs to install the industrial 3D simulation software - MIoT.VC on the client, and then build a 3D model of the robot based on the robot's physical structure and import the 3D model of the robot into MIoT.VC. If the robot needs to process new materials, the robot is programmed offline. The user builds a 3D model of the new material to be processed based on its physical structure, and then imports the 3D model of the material to be processed into MIoT.VC, and sets the processing requirements of the material in MIoT.VC. In this way, the PLC can perform offline programming in MIoT.VC through the 3D model of the robot and the 3D model of the material to be processed. The specific process is as follows:

[0026] The PLC first instructs MIoT.VC to draw the processing trajectory of the 3D model of the material to be processed according to the 3D model and processing requirements of the material to be processed. The processing trajectory is a spatial continuous curve trajectory. The PLC then instructs MIoT.VC to use the robot inverse mechanism solver in the software to solve the point set corresponding to the robot 3D model walking along the above processing trajectory. The point set includes X points and their point information, where X>2. The point information includes the position coordinates, the time point when the end effector of the robot 3D model arrives at the point, and the posture data of the joints and end effector when the end effector of the robot 3D model arrives at the point.

[0027] The processing trajectory is a product production process with a continuous trajectory in space. Different processes have different requirements for accuracy. Some production processes have lower requirements for robot processing accuracy. High processing accuracy requirements will reduce the robot's production efficiency. In order to maximize production efficiency, the point selection criteria of the processing trajectory should be adjusted accordingly according to the accuracy requirements of the material to be processed. To this end, the user pre-builds the production process accuracy relationship table and the point-taking time cycle rules and uploads them to the PLC. The PLC receives the relationship table and rules and stores them in the local memory. The PLC queries the accuracy requirements corresponding to the production process of the material to be processed from the production process accuracy relationship table, and then queries the point-taking time cycle corresponding to the accuracy requirements from the point-taking time cycle rules, and then takes points from the point set in the client's MeiQing simulation (MIoT.VC) according to the point-taking time cycle. Take the point set containing 4000 points (i.e. X=4000) and the point information of each point, and the point acquisition time period is 20ms as an example. These 4000 points are arranged in chronological order. The PLC first takes out the starting point of the processing trajectory from the point set in the client's MIoT.VC simulation and stores it in the target point set in this PLC. The time point corresponding to the starting point is 0ms. Then, the arrival time of the end effector of the robot 3D model is taken out from the point set in the client's MIoT.VC simulation. The point with a time of 20ms is stored in the target point set in this PLC, and then the point with a time of 40ms when the end effector of the robot's three-dimensional model arrives is taken from the point set in the client's MeiQing simulation (MIoT.VC) and stored in the target point set in this PLC, and then the point with a time of 60ms when the end effector of the robot's three-dimensional model arrives is taken from the point set in the client's MeiQing simulation (MIoT.VC) and stored in the target point set in this PLC, and so on, taking a point every 20ms. For example, the PLC takes out 1000 (ie, Y=1000) points and stores them in the target point set in this PLC. Taking points according to the time period for taking points means that the entire processing trajectory is uniformly taken at fixed time intervals, without taking into account the curvature change of the processing trajectory, and the movement trajectory of the robot between two adjacent points is approximately a straight line. The trajectory formed by the points taken out in series may deviate greatly from the actual processing trajectory. To this end, PLC performs point selection (first point selection) based on the point selection time cycle, and performs the second point selection according to the curvature of each part of the processing trajectory. The detailed process is as follows:

[0028] PLC calculates the curvature of the machining trajectory at 1000 points in the target point set. The curvatures of these 1000 points are recorded as C1, C2, ... C 1000. The PLC compares the curvature of each point with the first threshold (0.01) and the second threshold (0.05) respectively. If the curvature of the point is less than 0.01, it means that the processing trajectory is close to a straight line in the trajectory segment where the point is located, that is, the trajectory segment changes little, and the points can be appropriately reduced. Therefore, the PLC removes the point from the target point set. If the curvature of the point is greater than 0.05, it means that the arc of the trajectory segment where the point is located is relatively large, that is, the trajectory segment changes greatly. If there are too few points, it is easy to produce a large deviation. Therefore, the PLC takes a point according to the preset point density. The point density is, for example, one point is taken every quarter of the point taking time period, that is, the PLC takes a point according to the point density of one point every interval of 20ms*1 / 4=5ms. From the above point set, for example, 3 points are taken before and after the point, and stored in the target point set in the PLC. In other embodiments, the above n can be changed to other values ​​greater than or equal to 1. Taking the case where the curvature of the point at which the end effector of the robot 3D model reaches the time point of 200ms as greater than the second threshold as an example, the PLC takes out the points corresponding to the arrival time points of 195ms, 190ms, and 185ms of the end effector of the robot 3D model from the point set corresponding to 200ms, and takes out the points corresponding to the arrival time points of 205ms, 210ms, and 215ms of the end effector of the robot 3D model from the point set corresponding to 200ms, and then stores these 6 points in the target point set in this PLC. After comparing the curvature of each point one by one and performing corresponding processing, the PLC outputs control instructions to the robot 3D model in the MIoT.VC in the client according to the latest target point set, so that the robot 3D model simulates the processing process, and then makes the MIoT.VC measure the deviation between the trajectory of the processing process and the above processing trajectory, and judge whether the deviation meets the accuracy requirements of the production process of the material to be processed. The deviation can be calculated as follows: take the starting point of the above-mentioned processing trajectory as the coordinate origin, construct an XY coordinate system, and based on the coordinate system, calculate the distance between each point in the processing trajectory point set and the corresponding point of the trajectory of the above-mentioned simulated processing process, and take the average value of these distance values ​​as the above-mentioned deviation. For example, if the accuracy requirement is an error value ≤1mm, if the deviation is ≤1mm, it meets the accuracy requirement, and the target point set is used as the processing trajectory point set, and transmitted to the PLC that controls the movement of the physical robot corresponding to the robot three-dimensional model through wireless communication, so that the PLC can control the physical robot to process the material to be processed according to the processing trajectory point set. If the deviation is greater than 1mm, it does not meet the accuracy requirement, shorten the point-taking time period and increase the point-taking density according to the preset adjustment rules.The adjustment rules of this embodiment are preset as follows: the point picking time period is shortened by half, and the point picking density is doubled. For example, the point picking time period of the above-mentioned material to be processed is shortened from 20ms to 10ms, and the point picking density is changed to taking one point every 2.5ms. After the PLC shortens the point picking time period and increases the point picking density, it clears the target point set, and then re-takes the corresponding number (for example, 2000) of points from the point set in the client's MeiQing simulation (MIoT.VC) according to the new point picking time period of 10ms and stores them in the target point set in this PLC, and then, on the basis of taking points according to the point picking time period of 10ms (the first point selection), based on the point picking density of taking one point every 2.5ms, the second point selection is performed according to the curvature of each part of the processing trajectory. The second point selection process refers to the above and will not be repeated here.

[0029] The above is only an implementation method of the invention, and does not limit the scope of patent protection. Those skilled in the art can make non-substantial changes or substitutions based on the invention, which still fall within the scope of patent protection.

Claims

1. A robot space continuous curve trajectory offline programming method, characterized in that: This method is executed by PLC and specifically includes the following steps: S1. After the robot 3D model and the 3D model of the material to be processed are imported into the 3D simulation software, the 3D simulation software is used to draw the processing trajectory of the 3D model of the material to be processed according to the 3D model and processing requirements of the material to be processed, and the processing trajectory is a continuous curve trajectory in space; S2. The 3D simulation software uses the robot back-calculation mechanism solver to solve the point set corresponding to the robot 3D model walking along the above processing trajectory, the point set includes X points and their point information, where X>2, and the point information includes the position coordinates, the time point when the end effector of the robot 3D model reaches the point, and the posture data of the joints and the end effector when the end effector of the robot 3D model reaches the point; S3. Determine the precision requirements of the production process of the material to be processed, and determine the time period of the point of the processing trajectory accordingly; S4. According to the above-mentioned point-taking time period, Y points and their point information are taken from the point set in the three-dimensional simulation software and stored in the target point set in the PLC, where Y <X; S5. Calculate the curvature of the machining trajectory at the above Y points. If the curvature of the point is less than the first threshold, remove the point and its point information from the target point set. If the curvature of the point is greater than the second threshold, take n points before and after the point in the point set in the three-dimensional simulation software and their point information according to the preset point density and store them in the target point set in the PLC, where n≥1. S6. Output the target point set as a processing trajectory point set, so that the PLC can control the robot to perform actual processing operations according to the processing trajectory point set; The method comprises the following steps: step S60 executed before step S6. According to the target point set, a control instruction is output to the robot three-dimensional model in the three-dimensional simulation software to simulate the processing process, and then the three-dimensional simulation software is made to measure the deviation between the trajectory of the processing process and the above processing trajectory and determine whether the deviation meets the above accuracy requirement. If the deviation meets the above accuracy requirement, step S6 is executed, otherwise: S7. Shorten the point-taking time period and increase the point-taking density according to the preset adjustment rules, and re-execute steps S4 to S60.

2. The robot space continuous curve trajectory offline programming method according to claim 1 is characterized in that: Step S6 specifically transmits the processing trajectory point set to the PLC that controls the movement of the physical robot corresponding to the robot three-dimensional model through wireless communication.

3. The robot space continuous curve trajectory offline programming method as claimed in claim 1, characterized in that: The method comprises the steps of: receiving a production process accuracy relationship table and a point-taking time cycle rule, wherein the production process accuracy relationship table includes a correspondence between each production process and the accuracy requirements, and the point-taking time cycle rule includes a point-taking time cycle corresponding to each accuracy requirement; Specifically, step S3 queries the precision requirement corresponding to the production process of the material to be processed from the above production process precision relationship table, and then queries the point-taking time period corresponding to the precision requirement from the point-taking time period rule.

4. The robot space continuous curve trajectory offline programming method as claimed in claim 1, characterized in that: The first threshold is 0.01, and the second threshold is 0.

05.

5. A computer-readable storage medium having an executable computer program stored thereon, characterized in that: The computer program is executed to implement the robot spatial continuous curve trajectory offline programming method as described in any one of claims 1 to 4.

6. A robot space continuous curve trajectory offline programming system, characterized by: It includes a PLC and a client that can run three-dimensional simulation software. The PLC communicates with the client to send control instructions to the three-dimensional simulation software. The PLC includes a central processing unit and a computer-readable storage medium as described in claim 5. The central processing unit of the PLC executes the computer program in the storage medium to implement the robot spatial continuous curve trajectory offline programming method as described in any one of claims 1 to 4.

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